What is the fundamental idea behind support vector machines

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Reference no: EM133536060

Assignment:

1. What is the fundamental idea behind Support Vector Machines?

2. What is a support vector?

3. Say you trained an SVM classifier with an RBF kernel. It seems to underfit the training set: should you increase or decrease γ (gamma)? What about C?

4. Train a classifier using Iris dataset and different attributes and different class (iris species).

5. Try training your classifier using all 4 attributes with a Gaussian kernel. Explore different values of hyperparameters and attempt to find the right combinations. Generate plots for different values of hyperparameters.

6. Build a model using all features and all 4 classes. Since SVM classifiers are binary.

7. Classifiers, you will need to use one-versus-all approach. Try to achieve the best accuracy by tuning hyperparameters; demonstrate with plots.

Reference no: EM133536060

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